Data scientists in the house

CUs should look to staff or collaborate with true technology inventors.

Artificial intelligence and machine learning are technologies developed by computer and data scientists. Data analysts have become key members of credit union staffs. Data scientists, however, are rare and expensive, so most credit unions rent them as needed instead of hiring them.

Only the largest financial institutions are investing in employing true data scientists, says Kirk Kordeleski, senior managing partner and chief strategy officer at BiG Consulting, Long Island, New York. The rest are hiring data analysts with math and computing skills to run data mining and analysis activity—but at the manager level, not the executive level, he reports. They are technology users, not inventors. “You can’t hire a math major and turn him or her into a data scientist by sending them to a two-week school. Some credit unions are trying this, but they underestimate the complexity of the activity,” he insists.

Hiring true data scientists is indeed a financial stretch for most CUs, agrees Sabeh Samaha, president/CEO of Samaha & Associates, Los Angeles. As such, they need to collaborate—to push vendors and organize credit union service organizations to develop AI products—so they can compete with what the very big banks are building, he advocates.


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